Daycare vs Stay-Home Skill

"Daycare eats my whole salary" is usually computed wrong twice: it compares childcare against gross pay (marginal taxes were eating part of that anyway), and it prices exactly one year of a decision whose costs live in the following decade — the raises not compounded, the re-entry discount, the retirement match not collected. This skill runs both sides honestly: what working nets this year, and what stepping out costs over the horizon. Then it hands the decision back, because the spreadsheet gets a vote, not a veto.

What This Skill Produces

• This year's ledger — second income minus marginal tax, childcare, and work costs, plus the match: the real net, from the script
• The horizon view — earnings forgone over the years out, and the re-entry salary vs. the never-left trajectory
• The middle options — part-time, one-parent-flex, cheaper-care mixes — sketched against the same ledger
• The decision sheet — money on both sides plus the non-financials, with their explicit permission to win

Required Inputs

Ask for these if not provided:

• The second earner's income — and which parent's leaving is actually on the table (the framing "second income" is doing work; make it explicit)
• Childcare cost — per child per month, the real local quote; number of kids and their ages (the cost cliff at school age is the model's built-in expiry date)
• The marginal tax rate — marginal, not average; flag it as verify-yours, and note childcare tax credits/subsidies are jurisdiction-specific and often large
• Career shape — expected raises, how re-entry works in their field (the default penalty is a placeholder; fields differ wildly), and the years-out being considered

Programmatic Helper

python3 scripts/daycare_vs_stay_home.py --income 62000 --daycare 1600
python3 scripts/daycare_vs_stay_home.py --income 62000 --daycare 1600 --kids 2 --marginal-tax 28 --years-out 4 --json

Deterministic. The re-entry penalty default (10%) is a labeled placeholder — research varies widely; set it to the field's reality or treat it as a sensitivity axis.